Evidence map›Paper›PMID 40846840›Full record

ArticleNPJ Parkinson's disease2025

Unraveling morphological brain network disparities Parkinsonian tremor from essential tremor: an artificial intelligence approach for clinical differentiation.

Moxuan Zhang, Siyu Zhou, Huizhi Wang, Pengda Yang, Jinli Ding, Xiaobo Wang, Xuzhu Chen, Chaonan Zhang, Anni Wang, Yuan Gao and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ Parkinson's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Moxuan Zhang *Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Siyu Zhou *Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Huizhi WangBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Pengda YangBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Jinli DingDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xiaobo WangDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xuzhu ChenDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Chaonan ZhangBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Anni WangBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Yuan GaoBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Qiang LiuBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Yueping LiDepartment of Neurology, Fujian Medical University Union Hospital, Fujian, China.
Tianqi XuDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Zeyu MaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yin JiangBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Lin ShiDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Chunlei HanDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yuchen JiDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. lyjychen@126.com.
Guoen CaiDepartment of Neurology, Fujian Medical University Union Hospital, Fujian, China. cgessmu@fjmu.edu.cn.
Tao FengCenter for movement disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. bxbkyjs@sina.com.
Jianguo ZhangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. zjguo73@126.com.
Fangang MengBeijing Neurosurgical Institute, Capital Medical University, Beijing, China. fgmeng@ccmu.edu.cn.

Funding

Foundation for Innovative Research Groups of the National Natural Science Foundation of China 82471265 and 81971070National Key Research and Development Program of China 2022YFC2405100the Fujian Province Joint Funds for the Innovation of Science and Technology 2019Y9070the Key Program of Science and Technique Foundation of Henan Province 241111310100
6 · The paper itself

Abstract

Tremor-dominant Parkinson's disease (TD) and Essential Tremor (ET) are the two most common types of tremors, posing huge challenges in diagnosis. This study was to investigate the pathogenesis of tremors using brain morphology and employ artificial intelligence techniques for distinguishing them. The cortical thickness differences in TD were primarily centered on the right precuneus, while in ET were mainly observed in the right medial orbitofrontal cortex. Subcortical analysis revealed that TD patients primarily exhibited an increase in pallidum, whereas ET patients showed a significant reduction in thalamus. Causal network analysis indicated that in TD, the right temporal lobe exhibited the highest out-degree, and gradually extended to motor control regions. In contrast, ET primarily exhibits initial changes in the prefrontal and occipital visual cortices. Finally, by incorporating these specific characteristics, we developed a machine learning model capable of accurately distinguishing between different tremor types, providing valuable insights for clinical practice.

Identifiers

PMID40846840
PMCPMC12373744

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.